Omics analyses of potato plant materials using an improved one-class classification tool to identify aberrant compositional profiles in risk assessment procedures

Esther Kok*, Jeroen van Dijk, Marleen Voorhuijzen, Martijn Staats, Martijn Slot, Arjen Lommen, Dini Venema, Maria Pla, Maria Corujo, Eugenia Barros, Ronald Hutten, Jeroen Jansen, Hilko van der Voet

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)

Abstract

The objective of this study was to quantitatively assess potato omics profiles of new varieties for meaningful differences from analogous profiles of commercial varieties through the SIMCA one-class classification model. Analytical profiles of nine commercial potato varieties, eleven experimental potato varieties, one GM potato variety that had acquired Phytophtora resistance based on a single insert with potato-derived DNA sequences, and its non-GM commercial counterpart were generated. The ten conventional varieties were used to construct the one-class model. Omics profiles from experimental non-GM and GM varieties were assessed using the one-class SIMCA models. No potential unintended effects were identified in the case of the GM variety. The model showed that varieties that were genetically more distant from the commercial varieties were recognized as aberrant, highlighting its potential in determining whether additional evaluation is required for the risk assessment of materials produced from any breeding technique, including genetic modification.

Original languageEnglish
Pages (from-to)350-358
JournalFood Chemistry
Volume292
Early online date24 Aug 2018
DOIs
Publication statusPublished - 15 Sep 2019

Fingerprint

Solanum tuberosum
Risk assessment
risk assessment
potatoes
taxonomy
DNA sequences
Genetic Techniques
Breeding
breeding methods
new variety
genetic engineering
nucleotide sequences

Keywords

  • Compositional analysis
  • Genetically modified organism
  • GMO
  • Omics profiling
  • Risk assessment

Cite this

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title = "Omics analyses of potato plant materials using an improved one-class classification tool to identify aberrant compositional profiles in risk assessment procedures",
abstract = "The objective of this study was to quantitatively assess potato omics profiles of new varieties for meaningful differences from analogous profiles of commercial varieties through the SIMCA one-class classification model. Analytical profiles of nine commercial potato varieties, eleven experimental potato varieties, one GM potato variety that had acquired Phytophtora resistance based on a single insert with potato-derived DNA sequences, and its non-GM commercial counterpart were generated. The ten conventional varieties were used to construct the one-class model. Omics profiles from experimental non-GM and GM varieties were assessed using the one-class SIMCA models. No potential unintended effects were identified in the case of the GM variety. The model showed that varieties that were genetically more distant from the commercial varieties were recognized as aberrant, highlighting its potential in determining whether additional evaluation is required for the risk assessment of materials produced from any breeding technique, including genetic modification.",
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language = "English",
volume = "292",
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Omics analyses of potato plant materials using an improved one-class classification tool to identify aberrant compositional profiles in risk assessment procedures. / Kok, Esther; van Dijk, Jeroen; Voorhuijzen, Marleen; Staats, Martijn; Slot, Martijn; Lommen, Arjen; Venema, Dini; Pla, Maria; Corujo, Maria; Barros, Eugenia; Hutten, Ronald; Jansen, Jeroen; van der Voet, Hilko.

In: Food Chemistry, Vol. 292, 15.09.2019, p. 350-358.

Research output: Contribution to journalArticleAcademicpeer-review

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AU - Kok, Esther

AU - van Dijk, Jeroen

AU - Voorhuijzen, Marleen

AU - Staats, Martijn

AU - Slot, Martijn

AU - Lommen, Arjen

AU - Venema, Dini

AU - Pla, Maria

AU - Corujo, Maria

AU - Barros, Eugenia

AU - Hutten, Ronald

AU - Jansen, Jeroen

AU - van der Voet, Hilko

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